The present embodiments relate to a method for integrating semantic data processing (e.g., in automation devices).
Field devices, or devices that operate based on microcontrollers (e.g., intelligent sensors, actuators and control units in automation or in a vehicle), are known in the prior art. As the complexity of automation installations increases, there is an increasing need to equip devices with an ability to process data in a structured and interpretable form together with a semantic description (e.g., for data processing similar to the principles of a “semantic web”).
Semantic data processing in devices is desired (e.g., in order to facilitate engineering of the devices) to avoid or detect errors during operation and to optimize automation installations by optimally parameterizing the devices.
Semantic data processing that is currently widespread in the field of sophisticated information processing is operated based on ontologies. Ontologies are a knowledge representation for a defined area of knowledge (e.g., a domain) with the aim of interchanging and using knowledge in a machine-readable form. An ontology provides far-reaching possibilities for forming properties (e.g., relations) between classes (e.g., concepts) of the domain, and provides the methods required for semantic data processing. On account of data-related powerfulness of ontologies, working with ontologies requires a computing environment with ample resources.
Techniques of the semantic web have been transferred to semantic data processing of devices and other automation components. However, processing of semantic data based on ontologies is not provided because of the restricted resources of devices. The restricted resources may include a comparatively small memory area, a narrow communication bandwidth, and a CPU or microcontroller with few resources as a central computing unit.
Semantic data processing that is “lighter” (e.g., lightweight) in comparison is based on a known data model called the “Resource Description Framework” (RDF). The RDF data model has formal semantics based on directed graphs. The data in the data model is modeled as triples. Triples are an elementary statement that includes a subject, predicate and object. A semantic repository, or a triple store among experts, are known for storing RDF triples. Triple stores may also be referred to as μRDF in devices equipped with a limited storage space and computing power range. The standardized data format “Efficient XML Interchange” (EXI) is suitable for implementing a μRDF on devices.
Description languages for specifying data formats and the methods for processing the data are known. One known description language is “Extensible Markup Language” (XML). XML is used to describe hierarchically structured data in text form or plain text. The XML description language is used to interchange data between computer systems in a platform-independent manner. On account of the textual nature of XML, XML may be read by machines and by persons. Schemes used to describe a structure and to define data types are also known. These schemes are based on a description language (e.g., XML), and the schemes are referred to as description language schemes. A scheme for using XML data is also known as an XML Scheme Definition (XSD).
Rapid interchange of data between computer systems, and/or rapid internal data processing, is/are often required and cannot be achieved using a textual description language such as XML. Binary representations of XML were therefore proposed. Such a binary representation is the above-mentioned EXI interchange format that may be processed more quickly than text-based XML data and requires less transmission bandwidth when interchanging data between computer systems. Moreover, use of EXI is not restricted only to a binary representation of XML, and EXI may be used as an interchange format for processing and transmitting any desired semi-structured data.
The EXI binary representation displays advantages (e.g., during use in devices). Devices may be set up for device-internal processing of data in the text-based XML format, or in the EXI interchange format, but may interchange data with one another via corresponding communication interfaces based on binary data (e.g., binary data according to EXI specifications).
The EXI binary representation is particularly efficient if EXI grammar has been defined (e.g., grammar that best represents a semantic representation or description of the data). This grammar is usually produced from the XML schemes explained above. The more specific this grammar (e.g., with regard to the structure of the data, contents of the data, data types), the more efficient and compact coding of the grammar and the grammar implementation are.
However, a semantic description of devices is currently not available in the majority of cases. At present, such descriptions are defined only experimentally in an ad-hoc manner in an engineering tool, and the semantic descriptions remain only in the engineering tool environment in a proprietary format.
In contrast, it would be desirable to use widespread ontologies (e.g., from the automation domain) in the implementation or engineering of devices.